Director of Product, Lab

This is a player-coach role. You'll build and lead the Lab function while personally owning 1–2 of the highest-leverage bets.

Your job is to reduce uncertainty, not ship features. You'll own ideas end-to-end — from hypothesis framing through fast experiments to explicit investment decisions: scale, pivot, or kill. Most ideas should die early. A few may graduate into Core or New Products with strong evidence behind them.

Success = learning velocity, decision quality, and team leverage — not output volume or adoption.

Key Responsibilities

• Portfolio & Strategy: Own the Lab bet portfolio. Size opportunities, set entry/exit criteria, and make decisive scale/iterate/kill calls. Maintain a visible exploration backlog.

• Experimentation: Frame experiments around the single riskiest assumption. Define kill criteria before building. Choose the right fidelity (prototype, spike, wizard-of-oz, no-code, live pilot). Ship fast and protect learning speed.

• Investment Decisions: Synthesize results into opinionated recommendations. Communicate what was tested, learned, and what remains unknown. Kill zombie initiatives — every experiment ends with a decision.

• Handoffs: When a bet shows strong signal, prepare validated hypotheses, evidence packs, risks, and a proposed scaling model. Transfer ownership fully.

• GTM & Partnerships: Source and close lighthouse pilots with clear scope, metrics, and off-ramps. Identify enabling partners and join strategic calls to move pilots to business validation.

• Team: Build a repeatable Lab Operating System (pipeline reviews, kill reviews, demo days, post-mortems).

• AI & Transparency: Use AI tools to accelerate research, synthesis, and prototyping. Explore AI-enabled product ideas with a realistic lens on cost, data, and accuracy. Publish decision memos and share failed experiments openly.

What Great Looks Like in 12 Months

• 3–5 high-risk bets tested with clear outcomes (scaled, iterated, or killed with rationale)

• 1–2 bets graduated to New Products or Core with evidence packs and clean handoffs

• A transparent kill list that saves months of misdirected effort

• A functioning Lab team with clear ownership, experiment discipline, and stakeholder trust

• A repeatable Lab Operating System that compounds learning

Requirements

Experience (Must-Have)

• 8–10+ years in Product with a proven 0→1 track record

• Personally owned multiple high-risk bets with explicit go/kill decisions

• 3+ years managing PMs (player-coach or group lead)

• Fluency across validation tools: discovery, prototypes, engineered MVPs — knows when each is appropriate

• Cross-functional leadership across Eng/Design/Analytics and GTM; comfort in pre-sales/pilot settings

• Experience where learning speed mattered more than polish and real downside risk was present

AI & Technical Judgment (Critical)

• Hands-on experience using AI as a product-building and exploration tool

• Can prototype with LLMs, APIs, or modern tooling and ship a functional prototype quickly

• Able to scope AI experiments realistically and judge feasibility without full engineering validation

• Can spot capability shifts and turn them into testable hypotheses

• Evaluates build vs. buy vs. partner decisions

This background often comes from: founder/co-founder roles, early-stage startups, internal labs/innovation teams, or new market bets inside larger companies.

Bonus

• Ex-founder with a clear ship/scale/kill story and measurable outcomes

• Payments, fintech, e-commerce, or nonprofit domain experience

• EU market familiarity (PSD2/SCA, data/privacy norms) and additional languages

This Role Is Not For You If…

• Your background is mostly in roadmap-driven delivery with stable scope

• You prefer incremental optimization of mature products

• You need long planning cycles and large teams to move

• You avoid pilot conversations or hesitate to ask customers for real commitments

• Ambiguity makes you uncomfortable